Abstract

Enhanced geothermal systems (EGS) differ from conventional reservoirs in that fractures and faults are central to the engineering problem. The coupled physical processes governing faulted and fractured reservoirs are complex and difficult to model. Traffic light systems (TLS), the current state-of-the-art for managing induced seismic hazard, have shown only limited success, in part due to fundamental limitations as reactionary protocols operating in stochastic systems.  

In this presentation, I address two questions that are critical to scaling up EGS: 

1. Can we leverage the permeability structure of fault zones to optimize geothermal energy? 

2. How can we develop transferable models and forecasts of fluid-induced fault slip? 

To address the first question, I present an in-depth analysis of the most recent stimulation at Fervo Energy’s Cape Station in Utah, demonstrating that large-scale faults form core components of the stimulated network. Next, I develop a probabilistic framework for seismic hazard management and embed it within a feedback control loop to design optimal injection strategies.  

The presentation highlights the importance of explicitly accounting for the geomechanical contact problem and argues for a shift in perspective on pre-existing faults: from treating them as a liability to recognizing them as a central design variable in future geothermal systems. 

Bio

Taeho Kim is a postdoctoral scholar at Stanford University in the Department of Energy Science & Engineering, working with Professor Eric Dunham in the Department of Geophysics. His research focuses on developing computational models of enhanced geothermal systems, with an emphasis on the coupled interactions between hydraulic fractures, pre-existing faults, and fluid pressure evolution. He also works with Prof. Hamdi Tchelepi on numerical implementations of sophisticated friction laws in GEOS for multiphase flow settings.

Prior to Stanford, he received his B.S. in Civil Engineering from the University of Michigan and his M.S. and Ph.D. in Applied Mechanics from Caltech. His doctoral thesis, Modeling Frictional Processes in the Presence of Fluids: From Earthquakes in the Laboratory to Induced Seismicity in Geothermal Reservoirs, received the Demetriades Award for Outstanding Thesis in Seismo-Engineering, Prediction, and Protection.

He currently serves as co-leader of the Statewide California Earthquake Center’s initiative on Advancing Simulations of Earthquakes and Aseismic Slip, where he leads community efforts to develop numerical benchmark problems for fault slip coupled with pressure diffusion driven by subsurface fluid injection.

Research/Related Papers

Kim, T., & Avouac, J. P. (2023). Stress‐based and convolutional forecasting of injection‐induced seismicity: Application to the Otaniemi geothermal reservoir stimulation. Journal of Geophysical Research: Solid Earth, 128(4), e2022JB024960. Link.

Kim, T., Gutiérrez-Oribio, D., Stefanou, I., Acosta, M., & Avouac, J. P. (2025). Single-well based control and optimization of hydraulic stimulation and induced seismicity: Application to the Otaniemi geothermal project. Geothermics, 132, 103396. Link. 

Kim, T., Im, K., & Avouac, J. P. (2025). Finite size effects on seismicity induced by fluid injection in a discrete fault network with rate‐and‐state friction. Journal of Geophysical Research: Solid Earth, 130(7), e2024JB030243. Link.